{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n",
      "cat miaomiao\n"
     ]
    }
   ],
   "source": [
    "# \n",
    "# animal\n",
    "# cat dog pig ...\n",
    "class Object():\n",
    "    def __init__(self):\n",
    "        self.id=0\n",
    "\n",
    "class Animal():\n",
    "    def __init__(self):\n",
    "        self.height=1.0 #public\n",
    "        self._age=10 # protected\n",
    "        self.__weight=100.0 # private\n",
    "        \n",
    "    def talk(self):        \n",
    "        print(self.__age)\n",
    "\n",
    "        pass\n",
    "\n",
    "    \n",
    "class Cat(Animal):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        pass\n",
    "    def talk(self):\n",
    "        print(self._age)\n",
    "        print(\"cat miaomiao\")\n",
    "\n",
    "class Dog(Animal):\n",
    "    def __init__(self):\n",
    "        pass\n",
    "    def talk(self):\n",
    "        print(\"cat wang wang\")\n",
    "\n",
    "class Pig(Animal):\n",
    "    def __init__(self):\n",
    "        pass\n",
    "    def talk(self):\n",
    "        print(\"cat aoao\")\n",
    "\n",
    "cat =Cat()\n",
    "cat.talk()\n",
    "cat._age\n",
    "# dog =Dog()\n",
    "# dog.talk()\n",
    "# pig =Pig()\n",
    "# pig.talk()\n",
    "\n",
    "\n",
    "def talk3times(animal):\n",
    "   \n",
    "    animal.talk()\n",
    "    animal.talk()\n",
    "    animal.talk()\n",
    "\n",
    "# talk3times(cat)\n",
    "\n",
    "def create():\n",
    "    cat =Cat()\n",
    "    dog =Dog()\n",
    "    pass\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Convolution_filter:\n",
    "    def __init__(self,filter_size=3):\n",
    "        self.filter_size=filter_size\n",
    "\n",
    "    def set_filter_size(self,filter_size=3):\n",
    "        self.filter_size=filter_size\n",
    "        pass\n",
    "    def image_filter(self):\n",
    "        pass\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.12 ('base')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "d56fdd98391d50c9892c0eb684d4fbc2504af24585a45598abfbc74a3570fa0a"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
